Sahra Sedigh

Structural Health Monitoring of Bridges Using Wireless Sensor Networks

Aging and degradation of transportation infrastructure pose significant safety concerns, especially in light of increased use of these structures. The economic downturn further exacerbates such concerns, especially for critical structures such as bridges, where replacement is infeasible and maintenance and repair are expensive. The US Federal Highway Administration has classified over 25% of the bridges in the United States as either structurally deficient or functionally obsolete, underscoring the importance of structural health monitoring (SHM) to ensure public safety. We give an overview of emerging wireless sensor networks (WSN) for autonomous SHM systems, their application, the power use and sources needed to support autonomy, and the type of communication that allows remote monitoring.

Modeling Cyber-Physical Systems with Semantic Agents

The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this paper, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. This model is used to represent the static structure and dynamic behavior of an intelligent water distribution network as a CPS case study.

A General Framework for Quantitative Modeling of Dependability in Cyber-Physical Systems: A Proposal for Doctoral Research

The overarching objective of the proposed doctoral researches to build a qualitative and quantitative understanding of dependability in cyber physical systems (CPS).The existing body of knowledge includes frameworks and techniques for assessment, modeling, and simulation of the physical and cyber infrastructures, respectively, but such isolated analysis is incapable of fully capturing the interdependencies between these infrastructures. Understanding these interdependencies is a critical precursor to accurate representation and modeling of the CPS as a whole, especially with respect to dependability.The physical water distribution infrastructure, coupled with the hardware and software that support intelligent water allocation, comprise the model CPS that will be used as a case study for the proposed research. A preliminary literature review has been carried out on dependability modeling for CPS, with very sparse results. Allocation algorithms for water distribution have also been investigated,with game theory appearing to hold the most promise.An agent-based approach is suggested for linking the cyber and physical layers, where the agents retrieve information from sensors monitoring the physical components and provide this information to the cyber components. Fault injection will be used to investigate the propagation of failures between the cyber and physical layers. Markovian models will be used to capture the manifestation of cyber and/or physical faults as failures in water allocation, or containment of contaminants.

Reliability modeling for the advanced electric power grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify power flow locally within a grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the power grid to achieve higher dependability. The goal is to reroute power in the event of transmission line failure. Such a system, over a widespread area, is a cyber-physical system. The overall reliability of the grid is a function of the respective reliabilities of its two major subsystems, namely, the FACTS network and the physical components that comprise the infrastructure. This paper presents a mathematical model, based on the Markov chain imbeddable structure, for the overall reliability of the grid. The model utilizes a priori knowledge of reliability estimates for the FACTS devices and the communications links among them to predict the overall reliability of the power grid.

Reliability Analysis for the Advanced Electric Power Grid: From Cyber Control and Communication to Physical Manifestations of Failure

The advanced electric power grid is a cyber-physical system comprised of physical components, such as transmission lines and generators, and a network of embedded systems deployed for their cyber control. The objective of this paper is to qualitatively and quantitatively analyze the reliability of this cyber-physical system. The original contribution of the approach lies in the scope of failures analyzed, which crosses the cyber-physical boundary by investigating physical manifestations of failures in cyber control. As an example of power electronics deployed to enhance and control the operation of the grid, we study Flexible AC Transmission System (FACTS) devices, which are used to alter the flow of power on specific transmission lines. Through prudent fault injection, we enumerate the failure modes of FACTS devices, as triggered by their embedded software, and evaluate their effect on the reliability of the device and the reliability of the power grid on which they are deployed. The IEEE118 bus system is used as our case study, where the physical infrastructure is supplemented with seven FACTS devices to prevent the occurrence of four previously documented potential cascading failures.

A Semantic Agent Framework for Cyber-Physical Systems

The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++.

An Agent-Based Approach to Reconciling Data Heterogeneity in Cyber-Physical Systems

Computing and communication devices in any cyber-physical system (CPS) of non-trivial scale exhibit significant heterogeneity. Critical infrastructure systems, which are prime examples of CPSs, are no exception. The extent of networking capability, decentralized control, and more generally, integration between the cyber and physical infrastructures can vary greatly within a large-scale CPS. Other manifestations of heterogeneity in CPSs are in the resolution, syntax, and semantics of data collected by sensors from the physical infrastructure. Similar challenges complicate the use of databases that maintain past sensor data, device settings, or information about the physical infrastructure. The work presented in this paper aims to address these challenges by using the summary schemas model (SSM), which enables heterogeneous data sources to be queried with an unrestricted view and/or terminology. This support for imprecise queries significantly broadens the scope of data that can be used for intelligent decision support and carries the promise of increased reliability and performance for the CPS. We seek to ensure that ambiguity and imprecision do not accompany this expanded scope. %a.r.(note imprecise query also may bring ambiguity and not exact answer into the picture) The ultimate goal of a CPS is to fortify and streamline the operation of its physical infrastructure. The success of this task is contingent upon correct and efficient interpretation of data describing the state of the physical components, and the constraints to which it is subject. To this end, we propose agent-based semantic interpretation services that extract meaningful and useful information from raw data from heterogeneous sources, aided by the SSM. The proposed approach is described in the context of intelligent water distribution networks, which are cyber-physical critical infrastructure systems responsible for reliable delivery of potable water. The methodology is general, and can be extended to a broad range of CPSs, including smart power grids and intelligent transportation systems.

Software-based analysis of the effects of electrostatic discharge on embedded systems

This paper illustrates the use of software for monitoring and recording the effects of electrostatic discharge (ESD) on the operation of embedded systems, with the goal of facilitating root-cause analysis of resulting failures. Hardware -- based scanning techniques are typically used for analyzing the effect of ESD on systems by identifying physical coupling paths. This paper proposes software techniques that monitor registers and flags associated with peripherals of embedded systems to detect faults associated with the effects of ESD. A lightweight, cost-effective, and non-intrusive software tool has been developed that monitors and records the status of all registers associated with a designated peripheral under test, identifying the fault propagation caused by ESD in the system, and visually presenting the resulting errors. The tool has been used to detect and visually summarize ESD-induced errors on the SD card peripheral of the S3C2440 development board, using local injection and system-level scanning. Root-cause analysis of these faults can potentially assist in identification of coupling paths of electromagnetic interference, as well as determination of areas of the hardware that are more vulnerable to ESD.

The Advanced Electric Power Grid: Complexity Reduction Techniques for Reliability Modeling

The power grid is a large system, and analyzing its reliability is computationally intensive, rendering conventional methods ineffective. This paper proposes techniques for reducing the complexity of representations of the grid, resulting in a mathematically tractable problem to which our previously developed reliability analysis techniques can be applied. The IEEE118 bus system is analyzed as an example, incorporating cascading failure scenarios reported in the literature.

Modeling of Autonomous Vehicle Operation in Intelligent Transportation Systems

The past decade has seen autonomous vehicles become the subject of considerable research and development activity. The majority of these advances have focused on individual vehicles, rather than the interactions that result when autonomous (unmanned) and conventional (manned) vehicles come together in an intelligent transportation system. The robustness of autonomous vehicles to contingencies caused by unpredictable human behavior is a critical safety concern. Assuring the reliability, availability, security, and similar non-functional attributes of autonomous vehicles is just as critical.